The present invention relates to demodulation of multilevel signals and, more particularly, to methods of demodulating multilevel signals to obtain a binary value for a signal that includes bits produced by hard and soft decisions.
The goal of a digital communication system is to deliver information represented by a sequence of binary symbols through a physical communication channel to a receiver. The symbols are mapped by a digital modulation process into signals selected to match the characteristics of the communication channel. Multilevel digital modulation processes are often used in applications requiring a high bit rate in a channel of limited bandwidth. Multilevel modulation maps symbols into a plurality of waveforms so that any time the transmitted signal represents a plurality of symbols. Phase-shift keying is a linear modulation method used in multilevel digital modulation. Two equal sinusoidal components (in-phase (I) and quadrature (Q)) at the same frequency, but 90° apart in phase, are added to produce a single wave at the same frequency with four unique phases (90° apart) corresponding to the I and Q components of the signal. Each of the sinusoidal components can represent either a digital “1” or a digital “0” as designated by a 180° phase shift. Phase-shift keying may also be combined with pulse amplitude modulation (PAM) in a modulation technique known as quadrature amplitude modulation or QAM in which each of the phases has an amplitude that is the vector sum of the amplitudes of the in-phase and quadrature components. A two-bit quantization of both the in-phase and quadrature components results in 16 unique states of the carrier of each modulated symbol permitting transmission of four bits per symbol. The resulting combinations of in-phase and quadrature components are referred to as a signal constellation and the number of signals in the constellation indicates the order of the digital modulation. For example, 16-QAM indicates a constellation of 16 signal vectors with each of the I and Q components represented by two bits and 64-QAM indicates a three-bit quantization of both I and Q to produce 64 unique signal levels or a 64 signal vector constellation.
A second important aspect of a digital communication system is the detection and correction of bit errors that result from the transfer of the information in an imperfect medium. In some systems, errors are detected and corrected by retransmission of the information. In other systems, retransmission is not acceptable and error detection is combined with error correction using forward error correction (FEC) coding techniques. With FEC additional symbols are systematically inserted into the data stream to add redundancy to the transmission. In addition, adjacent individual bits of the transmitted message may be dispersed in the data stream by interleaving. Interleaving reduces susceptibility to burst errors that can corrupt sequential bits in the stream. FEC coding commonly employs block coding, convolutional coding, or turbo-coding which interleaves the data stream between a plurality of encoders.
At the receiver, the acquired signals are demodulated and decoded. The FEC decoder applies an algorithm to the demodulated signal to determine the most likely symbols of the original message even though the acquired signal may include data errors. The Viterbi algorithm is a commonly used and efficient algorithm for decoding convolutional coded or turbo-coded bitstreams. The convolutional coding and turbo-coding processes can be represented by a trellis diagram where each node of the diagram represents a coding interval. The decoder attempts to retrace the path through the trellis take by the encoder in encoding the original data. The Viterbi algorithm relies on calculation of a path metric or measure of the likelihood for all paths through the trellis that could have been taken at each coding interval. The decoder then discards all but the most likely path and initiates decoding of the next interval. The path metrics can be computed using binary or hard decision information related to the modulation symbol. Alternatively, the bits of the modulation symbol obtained from the demodulator may be mapped into values reflecting an estimate of the received symbol and an indication of the reliability of this estimate or soft decision information. For example, if a signal employs three-bit quantization, two of the bits might be used as a reliability measure. It is well known that FEC decoders such as the Viterbi decoder make better decisions if information about the quality of the acquired signal (soft information) is available during decoding.
Hong et al., U.S. Pat. No. 5,134,635, describe a soft-decision Viterbi decoder that uses channel state information to decode convolutionally encoded information transmitted with a 16-QAM multilevel signal. Bit metrics are produced for each of the four bits of the demodulated acquired signal. The two bits of the bit metric reflect a level of reliability or likelihood that the corresponding bit of the demodulated signal is either a binary “1” or binary “0”. The lower the value of the specific bit metric the higher the likelihood that the corresponding bit is correctly represented by the value specified for the bit. The Viterbi decoder makes the final determination of the value of each binary digit of the data stream from the sequence of demodulated signal values and the corresponding bit metrics. However, the method is limited to extraction of soft decision information from a 16-QAM multilevel signal. The method is not generalized for use with higher order QAM signal constellations or with PSK modulated signals.
Le Goff et al., in a paper entitled TURBO-CODES AND HIGH SPECTRAL EFFICIENCY MODULATION, Proc. of International Communications Conference, pp. 645–649, IEEE, 1994, disclose a coding scheme combining turbo-codes and multilevel signal modulation. A method of approximating bit metrics or log likelihood ratios (LLRs) for the constituent bits of a QAM or PSK symbol is described. This method provides a generalized method of extracting soft decision information from the modulated signal that produces the results of Hong et al. when applied to 16-QAM signals. The method yields soft information for each of the bits of the demodulated signal. While the availability of information based on soft decisions is beneficial to the decoding process, soft information increases the quantity of data that must be processed during decoding which increases the cost and complexity of the decoder. In some applications, the additional cost and complexity of the decoder may not be justified. Satisfactory decoding may be accomplished with bits obtained by a mixture of hard and soft decisions concerning the multilevel signal. The method of LeGoff et al. does not provide for a demodulated signal that is represented by a mixture of bits based on hard and soft decisions.
What is desired, therefore, is a method of demodulating a multilevel, acquired signal to produce a binary representation of the signal comprising bits resulting from both hard and soft decisions concerning the value of the acquired signal.